Large Language Models (LLMs) have made significant progress in the field of Natural Language Processing (NLP), shining in applications such as text generation, summarization, and question answering. However, the reliance of LLMs on token-level processing (predicting one word at a time) presents some challenges. This method contrasts with human communication, which typically operates at higher levels of abstraction, such as sentences or ideas. Token-level modeling also struggles in tasks that require understanding long contexts and may produce inconsistent outputs.